1. Field of the Invention
The present invention relates to a system and method for using adaptive matched filter signal parameter measurement during signal processing and, more particularly, to a system and method that enables improved matched filter parameter measurements at minimal cost by allowing for adaptive control, configuration and dynamic operation of pre-filters.
2. Description of the Related Art
Many communication systems use radio frequency (RF) signals to transfer data. Generally, systems designed to receive and process these RF signals are designed to detect RF signals in a particular range. When a RF signal is received, systems often process the signal before further use. For example, a system may convert analog signals to digital or vice versa. The system may have to optimize the data received or remove extraneous data. After the system processes the data, it may use the data, pass it along to another system or provide it to a user through an interface. Therefore, for a system to work efficiently, it is important to accurately process any received signals. One known method for signal processing is signal parameter measurement. Signal parameter measurement extracts information from the signal to allow the system to process the data more efficiently.
Signal parameter measurement methods are used by many different types of systems, such as radar systems, collection systems, military communications, and some wireless communications. Conventional systems usually only use the presence of signal energy to configure their pre-filters with fixed bandwidth schemes. These fixed bandwidths schemes or the use of tuning approaches produce sub-optimal results that require additional signal filter paths for each measurement. Accordingly, conventional methods often include arcane designs and inefficient architectures.
Some conventional methods optimize the signal parametrics, for example, by using differing bandwidths and tuning and gain control features that depend upon the nature of the parameter to be measured or estimated. However, these methods only improve efficiency slightly. Furthermore, these techniques do not improve the flexibility of such systems to process a variety of signals on the same path. Thus, there is a need for a more optimal and robust system that has the flexibility to handle a variety of different signal types.